Your team is developing a solution that will make use of DynamoDB tables.
Currently, the application is designed to perform scans on the entire table.
Which of the following can be done to re-design and improve the application's performance when it interacts with the DynamoDB table? Choose 2 answers from the options given below.
Click on the arrows to vote for the correct answer
A. B. C. D.Answer - A and D.
The AWS Documentation mentions the following.
Many applications can benefit from using parallel Scan operations rather than sequential scans.
For example, an application that processes a large table of historical data can perform a parallel scan much faster than a sequential one.
Multiple worker threads in a background "sweeper" process could scan a table at a low priority without affecting production traffic.
In each of these examples, a parallel Scan is used in such a way that it does not starve other applications of provisioned throughput resources.
If possible, you should avoid using a Scan operation on a large table or index with a filter that removes many results.
Also, as a table or index grows, the Scan operation slows.
The Scan operation examines every item for the requested values and can use up the provisioned throughput for a large table or index in a single operation.
For faster response times, design your tables and indexes so that your applications can use Query instead of Scan.
Option B is incorrect since having larger tables would make the issue worse.
Option C is incorrect since this would not help in the issue.
For more information on scans and queries, please refer to the below URL-
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-query-scan.htmlThe correct answers are A and D.
A) Consider using parallel scans: Scanning an entire DynamoDB table can be time-consuming and expensive, especially for larger tables. Parallel scans can help to reduce the time it takes to scan the entire table by dividing the work into smaller parts and scanning multiple segments of the table at the same time. This can significantly improve the performance of your application when interacting with DynamoDB tables.
D) Consider using queries: Querying is a more efficient way to retrieve data from DynamoDB compared to scanning an entire table. Queries retrieve only the items that match a specified partition key value or a combination of partition key value and sort key value. In contrast, scanning retrieves all items in a table, which can be wasteful if you only need a subset of the data. Therefore, using queries instead of scans can help to improve the performance of your application when interacting with DynamoDB tables.
B) Consider using large tables: Using large tables does not improve performance. Instead, it can make it harder to manage and maintain your data.
C) Consider using string partition keys: Using string partition keys does not necessarily improve performance. Instead, it can affect the data distribution across partitions and may lead to uneven data distribution and hot partitions. Therefore, choosing the right partition key for your data is more important than using a specific data type such as strings.